Prochain séminaire pan-canadien de l'IRC-CNRC; Conférence ICBEST 2010 à Vancouver; Hommage à Armand Patenaude; Un nouvel outil de calcul des charges dues au vent exercées sur les toits; L'IRC-CNRC développe en sciences du bâtiment et de la santé; Archivage des autres numéros d'Échos techniques; Le CNRC entreprend une nouvelle initiative sur les bioproduits utilisés en construction
Bibliographic record
Abstract
In 2009-10 The NRC-IRC seminars presented across Canada, also known as Building Science Insight Seminar Series will be about Energy efficiency in Buildings, with a particular emphasis on new tools and technologies. The next International Conference on Building Envelope Systems and Technologies (ICBEST) takeing place from June 27 to 30th, 2010 in Vancouver will be a forum for leaders in research, construction practice and academics to exchange information and discuss recent developments in building envelope engineering. At the 12th Building Science and Technology conference held in Montreal from May 6th to 8th, the Quebec Building Envelope Council give the new Armand Patenaude Award to 6 outstanding individuals. NRC-IRC established a new network to bring together the many Canadian building science and health sciences researchers to improve building design, construction, operation and maintenance. Researchers at NRC have started a new R&D initiative on bioproducts for application in construction.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.187 | 0.052 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".